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Kinds of intelligence: types, tests and meeting the needs of society
José Hernández-Orallo · Zoubin Ghahramani · Tomaso Poggio · Adrian Weller · Matthew Crosby

Thu Dec 07 02:00 PM -- 09:30 PM (PST) @ Beverly Theater
Event URL: http://www.kindsofintelligence.org »

Existing research in machine learning and artificial intelligence has been constrained by a focus on specific tasks chosen either for their perceived importance in human intelligence, their expected practical impact, their suitability for testing and comparison, or simply by an accident of research trends. However, the intelligence landscape extends far beyond our current capabilities, with many unexplored dimensions that present themselves as new opportunities for research. This symposium explores this landscape across three main topics: a broader perspective of the possible types of intelligence beyond human intelligence, better measurements providing an improved understanding of research objectives and breakthroughs, and a more purposeful analysis of where progress should be made in this landscape in order to best benefit society.

Go to the symposium website for the latest version of the schedule

Thu 2:00 p.m. - 2:05 p.m. [iCal]
Opening remarks
José Hernández-Orallo
Thu 2:05 p.m. - 2:35 p.m. [iCal]

Lucia Jacobs is a biologist and Professor of Psychology and Neuroscience at the University of California, Berkeley, where she leads the Laboratory of Cognitive Biology. She is interested in how a mind is created from the building blocks of learning over evolutionary time, starting at the beginning of multi-cellular time with the evolution of spatial navigation. She studies two domains: spatial cognition, how limbic brain structures, such as the hippocampus and olfactory systems, diversify and adapt to the demands of ecological niches, and “cognition in the wild”, the decision processes of tree squirrels as a model behavioral economic system.

Lucia Jacobs
Thu 2:35 p.m. - 3:05 p.m. [iCal]

Alison Gopnik is Professor of Psychology and Affiliate Professor of Philosophy at Berkeley University, California. She is known, amongst many other things, for developing the "theory theory", championing children's capacity to employ theory-based reasoning. She was the first cognitve scientist to apply probabilistic models to children’s learning, particularly using the causal Bayes net framework. In the past 15 years she has applied computational ideas to many areas of early cognitive development, including the learning of physical and social concepts.

Alison Gopnik
Thu 3:05 p.m. - 3:35 p.m. [iCal]

Demis Hassabis is co-founder and CEO of DeepMind and a Fellow of the Royal Society. In May 2017 DeepMind's AlphaGo convincingly beat the top ranked human player Ke Jie 3-0 in a match watched across the world. Up until DeepMind, Go had been previously viewed as a considerable challenge for AI, with a search space orders of magnitude larger than chess and no easy method known for positional evaluation. DeepMind's approach combined deep learning over many human games, with advances to convolutional networks, monte-carlo search and eventually self-play. Deepmind has pioneered research in deep learning and is focussed on applications of intelligence that will be beneficial to humanity.

Sarah-Jane Allen
Thu 3:35 p.m. - 4:00 p.m. [iCal]
Panel: "What can we learn from types of intelligent behaviour that are not usually covered by AI methods, and the other way round?" (Panel)
Sarah-Jane Allen, Alison Gopnik, Lucia Jacobs
Thu 4:30 p.m. - 5:00 p.m. [iCal]

Joshua Tenenbaum is Professor at the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology and is leader of the Computational Cognitive Science Group, where he studies computational models of human learning and inference. He has numerous influential papers, including 'How to Grow a Mind', exploring how computational models can address deep questions about the nature and origin of human thought. His work combines empirical methods and formal approaches with a focus on probabilistic models, and has narrowed the gap between AI and the capacities of human learners.

Josh Tenenbaum
Thu 5:00 p.m. - 5:30 p.m. [iCal]

Gary Marcus is a scientist, bestselling author, entrepreneur, and AI contrarian. He was CEO and Founder of the machine learning startup Geometric Intelligence, recently acquired by Uber. As a Professor of Psychology and Neural Science at NYU, he has published extensively in fields ranging from human and animal behavior to neuroscience, genetics, and artificial intelligence, often in leading journals such as Science and Nature. As a writer, he contributes frequently to the The New Yorker and The New York Times, and is the author of four books, including The Algebraic Mind, Kluge:The Haphazard Evolution of the Human Mind, and The New York Times Bestseller, Guitar Zero, and also editor of the recent book, The Future of the Brain: Essays By The World's Leading Neuroscientists, featuring the 2014 Nobel Laureates May-Britt and Edvard Moser.

Gary Marcus
Thu 5:30 p.m. - 6:00 p.m. [iCal]

Katja Hofmann is a researcher at the Machine Intelligence and Perception group at Microsoft Research Cambridge, where she is the lead researcher for Project Malmo. Using the popular game Minecraft as a platform, Project Malmo aims to develop artificial intelligences that can interpret complex environments and collaborate with other agents, including humans. A key goal of the project is to assist the broader research community in developing new approaches to reinforcement learning. Outside of Project Malmo, Katja works on applying machine learning to information retrieval in order to improve online search and recommendation systems.

Katja Hofmann
Thu 6:00 p.m. - 6:30 p.m. [iCal]
Panel: "How can we characterise the landscape of intelligent systems and locate human-like intelligence in it?" (Panel)
Josh Tenenbaum, Gary Marcus, Katja Hofmann
Thu 7:30 p.m. - 8:05 p.m. [iCal]

Cynthia Dwork, Gordon McKay Professor of Computer Science at the Harvard Paulson School of Engineering, Radcliffe Alumnae Professor at the Radcliffe Institute for Advanced Study, and Affiliated Faculty at Harvard Law School, uses theoretical computer science to place societal problems on a firm mathematical foundation. She has been awarded the Edsger W. Dijkstra Prize and the Gödel Prize.

Cynthia Dwork
Thu 8:05 p.m. - 8:40 p.m. [iCal]

David Runciman is Professor of Politics and Head of the Department of Politics and International Studies at the University of Cambridge. He writes regularly for the London Review of Books and has published numerous books including The Confidence Trap: A History of Democracy in Crisis. His interests include various aspects of contemporary political philosophy and contemporary politics and he has recently worked on the dangers of Artificial Intelligence and Artificial Agents. David is interested in the difference between robots and artificial corporations and markets as well as the effects of franchising out decisions to machines on democracy.

David Runciman
Thu 8:40 p.m. - 9:20 p.m. [iCal]
Panel: "Should we prioritize research on human-like AI or something different?" (Panel)
Cynthia Dwork, David Runciman, Zoubin Ghahramani
Thu 9:20 p.m. - 9:30 p.m. [iCal]
Closing remarks
Adrian Weller

Author Information

José Hernández-Orallo (Universitat Politècnica de València)
Zoubin Ghahramani (Uber and University of Cambridge)

Zoubin Ghahramani is Professor of Information Engineering at the University of Cambridge, where he leads the Machine Learning Group. He studied computer science and cognitive science at the University of Pennsylvania, obtained his PhD from MIT in 1995, and was a postdoctoral fellow at the University of Toronto. His academic career includes concurrent appointments as one of the founding members of the Gatsby Computational Neuroscience Unit in London, and as a faculty member of CMU's Machine Learning Department for over 10 years. His current research interests include statistical machine learning, Bayesian nonparametrics, scalable inference, probabilistic programming, and building an automatic statistician. He has held a number of leadership roles as programme and general chair of the leading international conferences in machine learning including: AISTATS (2005), ICML (2007, 2011), and NIPS (2013, 2014). In 2015 he was elected a Fellow of the Royal Society.

Tomaso Poggio (Massachusetts Institute of Technology)
Adrian Weller (University of Cambridge)

Adrian Weller is Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI, where he is also a Turing Fellow leading work on safe and ethical AI. He is a Senior Research Fellow in Machine Learning at the University of Cambridge, and at the Leverhulme Centre for the Future of Intelligence where he leads the project on Trust and Transparency. His interests span AI, its commercial applications and helping to ensure beneficial outcomes for society. He serves on several boards including the Centre for Data Ethics and Innovation. Previously, Adrian held senior roles in finance.

Matthew Crosby (Imperial College London)

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